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cijothomas
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chore: refactor integration tests and add metrics coverage (open-telemetry#2432)
Co-authored-by: Cijo Thomas <[email protected]>
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‎.gitignore‎

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lcov.info
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actual/*.json

‎Cargo.toml‎

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@@ -4,27 +4,32 @@ version = "0.1.0"
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edition = "2021"
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publish = false
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[dependencies]
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opentelemetry = { path = "../../../opentelemetry", features = ["metrics", "logs"] }
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opentelemetry_sdk = { path = "../../../opentelemetry-sdk", features = ["rt-tokio", "logs", "testing"] }
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opentelemetry-proto = { path = "../../../opentelemetry-proto", features = ["gen-tonic-messages", "trace", "logs", "with-serde"] }
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opentelemetry = { path = "../../../opentelemetry", features = [] }
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opentelemetry_sdk = { path = "../../../opentelemetry-sdk", features = ["rt-tokio", "testing"] }
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opentelemetry-proto = { path = "../../../opentelemetry-proto", features = ["gen-tonic-messages", "trace", "logs", "metrics", "with-serde"] }
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log = { workspace = true }
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tokio = { version = "1.0", features = ["full"] }
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serde_json = "1"
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testcontainers = "0.15.0"
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testcontainers = { version = "0.23.1", features = ["http_wait"]}
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once_cell.workspace = true
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anyhow = "1.0.94"
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ctor = "0.2.9"
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tracing-subscriber = "0.3.19"
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tracing = "0.1.41"
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[target.'cfg(unix)'.dependencies]
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opentelemetry-appender-log = { path = "../../../opentelemetry-appender-log", default-features = false}
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opentelemetry-otlp = { path = "../../../opentelemetry-otlp", default-features = false }
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opentelemetry-semantic-conventions = { path = "../../../opentelemetry-semantic-conventions" }
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[features]
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hyper-client = ["opentelemetry-otlp/hyper-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace", "opentelemetry-otlp/logs", "opentelemetry-otlp/metrics"]
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reqwest-client = ["opentelemetry-otlp/reqwest-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace","opentelemetry-otlp/logs", "opentelemetry-otlp/metrics"]
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reqwest-blocking-client = ["opentelemetry-otlp/reqwest-blocking-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace","opentelemetry-otlp/logs", "opentelemetry-otlp/metrics"]
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tonic-client = ["opentelemetry-otlp/grpc-tonic", "opentelemetry-otlp/trace", "opentelemetry-otlp/logs", "opentelemetry-otlp/metrics"]
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hyper-client = ["opentelemetry-otlp/hyper-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace", "opentelemetry-otlp/logs", "opentelemetry-otlp/metrics", "internal-logs"]
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reqwest-client = ["opentelemetry-otlp/reqwest-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace","opentelemetry-otlp/logs", "opentelemetry-otlp/metrics", "internal-logs"]
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reqwest-blocking-client = ["opentelemetry-otlp/reqwest-blocking-client", "opentelemetry-otlp/http-proto", "opentelemetry-otlp/trace","opentelemetry-otlp/logs", "opentelemetry-otlp/metrics", "internal-logs"]
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tonic-client = ["opentelemetry-otlp/grpc-tonic", "opentelemetry-otlp/trace", "opentelemetry-otlp/logs", "opentelemetry-otlp/metrics", "internal-logs"]
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internal-logs = []
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# Keep tonic as the default client
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default = ["tonic-client"]
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default = ["tonic-client", "internal-logs"]
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‎README.md‎

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# OTLP - Integration Tests
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This directory contains integration tests for `opentelemetry-otlp`. It uses
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[testcontainers](https://testcontainers.com/) to start an instance of the OTEL collector using [otel-collector-config.yaml](otel-collector-config.yaml), which then uses a file exporter per signal to write the output it receives back to the host machine.
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The tests connect directly to the collector on `localhost:4317` and `localhost:4318`, push data through, and then check that what they expect
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has popped back out into the files output by the collector.
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For this to work, you need a couple of things:
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* Docker, for the test container
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* TCP/4317 and TCP/4318 free on your local machine. If you are running another collector, you'll need to stop it for the tests to run

‎actual/README.md‎

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Output from the otel-collector goes here.

‎expected/different_metrics.json‎

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{
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"resourceMetrics": [
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{
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"resource": {
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"attributes": [
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{
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"key": "service.name",
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"value": {
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"stringValue": "metrics-integration-test"
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}
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}
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]
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},
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"scopeMetrics": [
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{
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"scope": {
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"name": "meter"
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},
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"metrics": [
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{
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"name": "counter_u64",
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"sum": {
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"dataPoints": [
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{
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"attributes": [
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{
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"key": "mykey1",
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"value": {
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"stringValue": "mydifferentval"
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}
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},
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{
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"key": "mykey2",
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"value": {
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"stringValue": "myvalue2"
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}
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}
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],
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"startTimeUnixNano": "1734094309366798000",
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"timeUnixNano": "1734094317871514000",
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"asInt": "15"
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}
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],
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"aggregationTemporality": 2,
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"isMonotonic": true
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}
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},
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{
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"name": "example_histogram",
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"histogram": {
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"dataPoints": [
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{
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"attributes": [
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{
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"key": "mykey3",
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"value": {
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"stringValue": "myvalue4"
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}
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}
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],
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"startTimeUnixNano": "1734094309366875000",
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"timeUnixNano": "1734094317871537000",
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"count": "1",
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"sum": 42,
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"bucketCounts": [
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"0",
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"0",
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"0",
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"0",
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"1",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0"
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],
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"explicitBounds": [
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0,
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5,
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25,
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50,
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250,
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1000,
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2500,
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10000
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],
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"min": 42,
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"max": 42
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}
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],
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"aggregationTemporality": 2
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}
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},
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{
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"name": "example_up_down_counter",
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"sum": {
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"dataPoints": [
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{
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"attributes": [
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{
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"key": "mykey5",
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"value": {
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"stringValue": "myvalue5"
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}
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}
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],
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"startTimeUnixNano": "1734094309366941000",
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"timeUnixNano": "1734094317871548000",
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"asInt": "-1"
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}
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],
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"aggregationTemporality": 2
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}
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}
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]
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}
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]
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}
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]
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}

‎expected/metrics.json‎

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{
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"key": "service.name",
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"value": {
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"stringValue": "my.service"
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"stringValue": "metrics-integration-test"
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}
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}
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]
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},
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"scopeMetrics": [
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{
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"scope": {
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"name": "my.library",
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"version": "1.0.0",
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"attributes": [
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{
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"key": "my.scope.attribute",
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"value": {
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"stringValue": "some scope attribute"
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}
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}
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]
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"name": "meter"
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},
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"metrics": [
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{
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"name": "my.counter",
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"unit": "1",
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"description": "I am a Counter",
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"metadata": [],
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"name": "counter_u64",
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"sum": {
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"aggregationTemporality": 1,
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"isMonotonic": true,
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"dataPoints": [
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{
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"asDouble": 5,
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"startTimeUnixNano": "1544712660300000000",
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"timeUnixNano": "1544712660300000000",
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"attributes": [
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{
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"key": "my.counter.attr",
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"key": "mykey1",
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"value": {
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"stringValue": "some value"
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"stringValue": "myvalue1"
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}
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},
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{
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"key": "mykey2",
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"value": {
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"stringValue": "myvalue2"
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}
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}
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],
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"exemplars": [],
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"flags": 0
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"startTimeUnixNano": "1734094309366798000",
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"timeUnixNano": "1734094317871514000",
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"asInt": "10"
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}
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]
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],
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"aggregationTemporality": 2,
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"isMonotonic": true
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}
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},
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{
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"name": "my.gauge",
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"unit": "1",
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"description": "I am a Gauge",
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"metadata": [],
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"gauge": {
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"name": "example_histogram",
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"histogram": {
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"dataPoints": [
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{
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"asDouble": 10,
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"startTimeUnixNano": "1544712660300000000",
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"timeUnixNano": "1544712660300000000",
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"attributes": [
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{
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"key": "my.gauge.attr",
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"key": "mykey3",
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"value": {
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"stringValue": "some value"
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"stringValue": "myvalue4"
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}
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}
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],
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"exemplars": [],
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"flags": 0
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"startTimeUnixNano": "1734094309366875000",
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"timeUnixNano": "1734094317871537000",
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"count": "1",
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"sum": 42,
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"bucketCounts": [
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"0",
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"0",
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"0",
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"0",
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"1",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0",
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"0"
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],
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"explicitBounds": [
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0,
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5,
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25,
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75,
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10000
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],
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"min": 42,
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"max": 42
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}
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]
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],
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"aggregationTemporality": 2
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}
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},
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{
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"name": "my.histogram",
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"unit": "1",
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"description": "I am a Histogram",
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"metadata": [],
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"histogram": {
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"aggregationTemporality": 1,
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"name": "example_up_down_counter",
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"sum": {
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"dataPoints": [
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{
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"startTimeUnixNano": "1544712660300000000",
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"timeUnixNano": "1544712660300000000",
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"count": 2,
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"sum": 2,
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"bucketCounts": [1,1],
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"explicitBounds": [1],
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"min": 0,
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"max": 2,
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"attributes": [
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{
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"key": "my.histogram.attr",
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"key": "mykey5",
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"value": {
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"stringValue": "some value"
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"stringValue": "myvalue5"
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}
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}
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],
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"exemplars": [],
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"flags": 0
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"startTimeUnixNano": "1734094309366941000",
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"timeUnixNano": "1734094317871548000",
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"asInt": "-1"
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}
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]
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],
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"aggregationTemporality": 2
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}
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}
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],
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"schemaUrl": "whatever"
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]
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}
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],
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"schemaUrl": "whatever"
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]
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}
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]
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}
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}

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